Table 5 Clinical trials of novel digital stethoscope and AI-assisted analysis

Detecting respiratory pathologies using CNN and variational autoencoders

CNN was used to classify chronic disease, non-chronic disease and healthy group

Chronic disease

[56]

Non-chronic disease

Healthy

Observational (completed)

Predicting honeycombing on HRCT by the acoustic characteristics of fine crackles

Acoustic properties of fine crackles distinguish the honeycombing from non-honeycombing group

Honeycombing

[57]

Non-honeycombing

Observational (completed)

Diagnosing interstitial pneumonia by analyzing inspiratory lung sounds recorded with phonopneumography

Spectral analysis of lung sounds is useful in the diagnosis and evaluation of the severity of IP

Interstitial pneumonia

[59]

Healthy

Observational (completed)

Evaluating Auscul-X, a Touch Free Digital Stethoscope

Multichannel, touch-free electronic stethoscope

COVID-19

NCT04570189

Observational (recruiting)

Collecting respiratory sound samples to diagnose COVID-19 patients

VOQX Electronic Stethoscope

COVID-19

NCT04910191

Sound signals are processed by machine learning algorithm

Interventional (recruiting)

Clinical Evaluation of Automatic Classification of Respiratory System Sounds

StethoMe stethoscope

Wheezing, rhonchi, crackle, lung sound

NCT04208360

AI software application

Observational (not yet recruiting)

Digital auscultation test—IPF data collection

Littmann Digital Stethoscope

Idiopathic pulmonary fibrosis

NCT03503188

3M Littmann Steth Assist software

Interventional (completed)

Respiratory auscultation of an open real-time tele-stethoscope system

Open real-time tele-stethoscope system

Respiratory/heart disease

NCT03596541

Respiratory crackle

Interventional (not yet recruiting)